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Massey DJ, Szpiech ZA, Goldberg A. Differentiating mechanism from outcome for ancestry-assortative mating in admixed human populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.06.597727. [PMID: 38895317 PMCID: PMC11185628 DOI: 10.1101/2024.06.06.597727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Population genetic theory, and the empirical methods built upon it, often assume that individuals pair randomly for reproduction. However, natural populations frequently violate this assumption, which may potentially confound genome-wide association studies, selection scans, and demographic inference. Within several recently admixed human populations, empirical genetic studies have reported a correlation in global ancestry proportion between spouses, referred to as ancestry-assortative mating. Here, we use forward genomic simulations to link correlations in ancestry between mates to the underlying mechanistic mate-choice process. We consider the impacts of two types of mate-choice model, using either ancestry-based preferences or social groups as the basis for mate pairing. We find that multiple mate-choice models can produce the same correlations in ancestry proportion between spouses; however, we also highlight alternative analytic approaches and circumstances in which these models may be distinguished. With this work, we seek to highlight potential pitfalls when interpreting correlations in empirical data as evidence for a particular model of human mating practices, as well as to offer suggestions toward development of new best practices for analysis of human ancestry-assortative mating.
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Affiliation(s)
| | - Zachary A Szpiech
- Department of Biology, Pennsylvania State University, USA 16801
- Institute for Computational and Data Sciences, Pennsylvania State University, USA 16801
| | - Amy Goldberg
- Department of Evolutionary Anthropology, Duke University, USA 27708
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2
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Mas-Sandoval A, Mathieson S, Fumagalli M. The genomic footprint of social stratification in admixing American populations. eLife 2023; 12:e84429. [PMID: 38038347 PMCID: PMC10776089 DOI: 10.7554/elife.84429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 11/22/2023] [Indexed: 12/02/2023] Open
Abstract
Cultural and socioeconomic differences stratify human societies and shape their genetic structure beyond the sole effect of geography. Despite mating being limited by sociocultural stratification, most demographic models in population genetics often assume random mating. Taking advantage of the correlation between sociocultural stratification and the proportion of genetic ancestry in admixed populations, we sought to infer the former process in the Americas. To this aim, we define a mating model where the individual proportions of the genome inherited from Native American, European, and sub-Saharan African ancestral populations constrain the mating probabilities through ancestry-related assortative mating and sex bias parameters. We simulate a wide range of admixture scenarios under this model. Then, we train a deep neural network and retrieve good performance in predicting mating parameters from genomic data. Our results show how population stratification, shaped by socially constructed racial and gender hierarchies, has constrained the admixture processes in the Americas since the European colonization and the subsequent Atlantic slave trade.
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Affiliation(s)
- Alex Mas-Sandoval
- Department of Life Sciences, Silwood Park Campus, Imperial College LondonLondonUnited Kingdom
- Department of Statistical Sciences, University of BolognaBolognaItaly
| | - Sara Mathieson
- Department of Computer Science, Haverford CollegeHaverfordUnited States
| | - Matteo Fumagalli
- Department of Life Sciences, Silwood Park Campus, Imperial College LondonLondonUnited Kingdom
- School of Biological and Behavioural Sciences, Queen Mary University of LondonLondonUnited Kingdom
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3
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COVID-19 in Latin America and the Caribbean Region: Symptoms and Morbidities in the Epidemiology of Infection. Curr Opin Pharmacol 2022; 63:102203. [PMID: 35255454 PMCID: PMC8896761 DOI: 10.1016/j.coph.2022.102203] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 01/21/2022] [Accepted: 02/01/2022] [Indexed: 01/06/2023]
Abstract
The COVID-19 pandemic has widespread economic and social effects on Latin America (LA) and the Caribbean (CA). This region, which has a high prevalence of chronic diseases, has been one of the most affected during the pandemic. Multiple symptoms and comorbidities are related to distinct COVID-19 outcomes. However, there has been no explanation as to why different patients present with different arrays of clinical presentations. Studies report that similar to comorbidities, each country in LA and the CA has its own particular health issues. Moreover, economic and social features have yet to be studied in detail to obtain a complete perspective of the disease in the region. Herein, the impact of demographic and economic characteristics in LA and the CA on COVID-19 are presented in combination with symptoms and comorbidities related to the disease as important aspects that can influence management and treatment.
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Versluys TMM, Flintham EO, Mas-Sandoval A, Savolainen V. Why do we pick similar mates, or do we? Biol Lett 2021; 17:20210463. [PMID: 34813721 DOI: 10.1098/rsbl.2021.0463] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Humans often mate with those resembling themselves, a phenomenon described as positive assortative mating (PAM). The causes of this attract broad interest, but there is little agreement on the topic. This may be because empirical studies and reviews sometimes focus on just a few explanations, often based on disciplinary conventions. This review presents an interdisciplinary conceptual framework on the causes of PAM in humans, drawing on human and non-human biology, the social sciences, and the humanities. Viewing causality holistically, we first discuss the proximate causes (i.e. the 'how') of PAM, considering three mechanisms: stratification, convergence and mate choice. We also outline methods to control for confounders when studying mate choice. We then discuss ultimate explanations (i.e. 'the why') for PAM, including adaptive and non-adaptive processes. We conclude by suggesting a focus on interdisciplinarity in future research.
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Affiliation(s)
- Thomas M M Versluys
- Georgina Mace Centre for the Living Planet, Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot, Berkshire SL5 7PY, United Kingdom
| | - Ewan O Flintham
- Georgina Mace Centre for the Living Planet, Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot, Berkshire SL5 7PY, United Kingdom
| | - Alex Mas-Sandoval
- Georgina Mace Centre for the Living Planet, Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot, Berkshire SL5 7PY, United Kingdom
| | - Vincent Savolainen
- Georgina Mace Centre for the Living Planet, Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot, Berkshire SL5 7PY, United Kingdom
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Chande AT, Rishishwar L, Ban D, Nagar SD, Conley AB, Rowell J, Valderrama-Aguirre AE, Medina-Rivas MA, Jordan IK. The Phenotypic Consequences of Genetic Divergence between Admixed Latin American Populations: Antioquia and Chocó, Colombia. Genome Biol Evol 2021; 12:1516-1527. [PMID: 32681795 PMCID: PMC7513793 DOI: 10.1093/gbe/evaa154] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/12/2020] [Indexed: 12/11/2022] Open
Abstract
Genome-wide association studies have uncovered thousands of genetic variants that are associated with a wide variety of human traits. Knowledge of how trait-associated variants are distributed within and between populations can provide insight into the genetic basis of group-specific phenotypic differences, particularly for health-related traits. We analyzed the genetic divergence levels for 1) individual trait-associated variants and 2) collections of variants that function together to encode polygenic traits, between two neighboring populations in Colombia that have distinct demographic profiles: Antioquia (Mestizo) and Chocó (Afro-Colombian). Genetic ancestry analysis showed 62% European, 32% Native American, and 6% African ancestry for Antioquia compared with 76% African, 10% European, and 14% Native American ancestry for Chocó, consistent with demography and previous results. Ancestry differences can confound cross-population comparison of polygenic risk scores (PRS); however, we did not find any systematic bias in PRS distributions for the two populations studied here, and population-specific differences in PRS were, for the most part, small and symmetrically distributed around zero. Both genetic differentiation at individual trait-associated single nucleotide polymorphisms and population-specific PRS differences between Antioquia and Chocó largely reflected anthropometric phenotypic differences that can be readily observed between the populations along with reported disease prevalence differences. Cases where population-specific differences in genetic risk did not align with observed trait (disease) prevalence point to the importance of environmental contributions to phenotypic variance, for both infectious and complex, common disease. The results reported here are distributed via a web-based platform for searching trait-associated variants and PRS divergence levels at http://map.chocogen.com (last accessed August 12, 2020).
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Affiliation(s)
- Aroon T Chande
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia.,IHRC-Georgia Tech Applied Bioinformatics Laboratory, Atlanta, Georgia.,PanAmerican Bioinformatics Institute, Valle del Cauca, Cali, Colombia
| | - Lavanya Rishishwar
- IHRC-Georgia Tech Applied Bioinformatics Laboratory, Atlanta, Georgia.,PanAmerican Bioinformatics Institute, Valle del Cauca, Cali, Colombia
| | - Dongjo Ban
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia.,PanAmerican Bioinformatics Institute, Valle del Cauca, Cali, Colombia
| | - Shashwat D Nagar
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia.,PanAmerican Bioinformatics Institute, Valle del Cauca, Cali, Colombia
| | - Andrew B Conley
- IHRC-Georgia Tech Applied Bioinformatics Laboratory, Atlanta, Georgia.,PanAmerican Bioinformatics Institute, Valle del Cauca, Cali, Colombia
| | - Jessica Rowell
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia
| | - Augusto E Valderrama-Aguirre
- PanAmerican Bioinformatics Institute, Valle del Cauca, Cali, Colombia.,Biomedical Research Institute (COL0082529), Cali, Colombia.,Universidad Santiago de Cali, Colombia
| | - Miguel A Medina-Rivas
- PanAmerican Bioinformatics Institute, Valle del Cauca, Cali, Colombia.,Centro de Investigación en Biodiversidad y Hábitat, Universidad Tecnológica del Chocó, Quibdó, Colombia
| | - I King Jordan
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia.,IHRC-Georgia Tech Applied Bioinformatics Laboratory, Atlanta, Georgia.,PanAmerican Bioinformatics Institute, Valle del Cauca, Cali, Colombia
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6
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St Clair D, Lang B. Schizophrenia: a classic battle ground of nature versus nurture debate. Sci Bull (Beijing) 2021; 66:1037-1046. [PMID: 36654248 DOI: 10.1016/j.scib.2021.01.032] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 07/29/2020] [Accepted: 10/13/2020] [Indexed: 01/20/2023]
Abstract
Much has been learned about the etiology and pathogenesis of schizophrenia since the term was first used by Eugene Bleuler over a century ago to describe one of the most important forms of major mental illness to affect mankind. Both nature and nurture feature prominently in our understanding of the genesis of the overall risk of developing schizophrenia. We now have a firm grasp of the broad structure of the genetic architecture and several key environmental risk factors have been identified and delineated. However, much of the heritability of schizophrenia remains unexplained and the reported environmental risk factors do not explain all the variances not attributable to genetic risk factors. The biggest problem at present is that our understanding of the causal mechanisms involved is still in its infancy. In this review, we describe the extent and limits of our knowledge of the specific genetic/constitutional and non-genetic/environmental factors that contribute to the overall risk of schizophrenia. We suggest novel methods may be required to understand the almost certainly immensely complex multi-level causal mechanisms that contribute to the generation of the schizophrenia phenotype.
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Affiliation(s)
- David St Clair
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, National Clinical Research Center for Mental Disorders, Changsha 410011, China; Institute of Medical Sciences, University of Aberdeen, Aberdeen AB25 2ZD, UK; Bio-X Life Science Research Center, Shanghai Jiao Tong University, Shanghai 200030, China.
| | - Bing Lang
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, National Clinical Research Center for Mental Disorders, Changsha 410011, China; Institute of Medical Sciences, University of Aberdeen, Aberdeen AB25 2ZD, UK.
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7
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Marca-Ysabel MV, Rajabli F, Cornejo-Olivas M, Whitehead PG, Hofmann NK, Illanes Manrique MZ, Veliz Otani DM, Milla Neyra AK, Castro Suarez S, Meza Vega M, Adams LD, Mena PR, Rosario I, Cuccaro ML, Vance JM, Beecham GW, Custodio N, Montesinos R, Mazzetti Soler PE, Pericak-Vance MA. Dissecting the role of Amerindian genetic ancestry and the ApoE ε4 allele on Alzheimer disease in an admixed Peruvian population. Neurobiol Aging 2021; 101:298.e11-298.e15. [PMID: 33541779 PMCID: PMC8122013 DOI: 10.1016/j.neurobiolaging.2020.10.003] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 09/29/2020] [Accepted: 10/01/2020] [Indexed: 01/21/2023]
Abstract
Alzheimer disease (AD) is the leading cause of dementia in the elderly and occurs in all ethnic and racial groups. The apolipoprotein E (ApoE) ε4 is the most significant genetic risk factor for late-onset AD and shows the strongest effect among East Asian populations followed by non-Hispanic white populations and has a relatively lower effect in African descent populations. Admixture analysis in the African American and Puerto Rican populations showed that the variation in ε4 risk is correlated with the genetic ancestral background local to the ApoE gene. Native American populations are substantially underrepresented in AD genetic studies. The Peruvian population with up to ~80 of Amerindian (AI) ancestry provides a unique opportunity to assess the role of AI ancestry in AD. In this study, we assess the effect of the ApoE ε4 allele on AD in the Peruvian population. A total of 79 AD cases and 128 unrelated cognitive healthy controls from Peruvian population were included in the study. Genome-wide genotyping was performed using the Illumina Global screening array v2.0. Global ancestry and local ancestry analyses were assessed. The effect of the ApoE ε4 allele on AD was tested using a logistic regression model by adjusting for age, gender, and population substructure (first 3 principal components). Results showed that the genetic ancestry surrounding the ApoE gene is predominantly AI (60.6%) and the ε4 allele is significantly associated with increased risk of AD in the Peruvian population (odds ratio = 5.02, confidence interval: 2.3-12.5, p-value = 2e-4). Our results showed that the risk for AD from ApoE ε4 in Peruvians is higher than we have observed in non-Hispanic white populations. Given the high admixture of AI ancestry in the Peruvian population, it suggests that the AI genetic ancestry local to the ApoE gene is contributing to a strong risk for AD in ε4 carriers. Our data also support the findings of an interaction between the genetic risk allele ApoE ε4 and the ancestral backgrounds located around the genomic region of ApoE gene.
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Affiliation(s)
| | - Farid Rajabli
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Mario Cornejo-Olivas
- Neurogenetics Research Center, Instituto Nacional de Ciencias Neurológicas, Lima, Peru; Center for Global Health, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Patrice G Whitehead
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Natalia K Hofmann
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | | | - Diego Martin Veliz Otani
- Neurogenetics Research Center, Instituto Nacional de Ciencias Neurológicas, Lima, Peru; Fogarty Northern Pacific Global Health Fellows Program, Lima, Peru; Fogarty Interdisciplinary Cerebrovascular Diseases Training Program in South America, Lima, Peru
| | | | - Sheila Castro Suarez
- CBI en Demencias y Enfermedades Desmielinizantes del Sistema Nervioso, Instituto Nacional de Ciencias Neurológicas, Lima, Peru; Atlantic Fellow of Global Brain Health Institute, San Francisco, CA, USA
| | - Maria Meza Vega
- CBI en Demencias y Enfermedades Desmielinizantes del Sistema Nervioso, Instituto Nacional de Ciencias Neurológicas, Lima, Peru; School of Medicine, Universidad Nacional Mayor de San Marcos, Lima, Peru
| | - Larry D Adams
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Pedro R Mena
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Isasi Rosario
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA; Dr. John Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Michael L Cuccaro
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA; Dr. John Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Jeffery M Vance
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA; Dr. John Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Gary W Beecham
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA; Dr. John Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | | | | | - Pilar E Mazzetti Soler
- Neurogenetics Research Center, Instituto Nacional de Ciencias Neurológicas, Lima, Peru; School of Medicine, Universidad Nacional Mayor de San Marcos, Lima, Peru
| | - Margaret A Pericak-Vance
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA; Dr. John Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA.
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8
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Fritz J, Lopez-Ridaura R, Choudhry S, Razo C, Lamadrid-Figueroa H. The association of Native American genetic ancestry and high-density lipoprotein cholesterol: A representative study of a highly admixed population. Am J Hum Biol 2020; 32:e23426. [PMID: 32329554 DOI: 10.1002/ajhb.23426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Revised: 03/11/2020] [Accepted: 04/08/2020] [Indexed: 11/12/2022] Open
Abstract
OBJECTIVE Hispanic populations typically show a high prevalence of dyslipidemias, especially of low high-density lipoproteins (HDLs) or HDL cholesterol. Highly admixed populations are ideal groups to clarify the role of genetic ancestry on HDL concentrations, isolating it from that of other factors. The objective of this study was to estimate the association between Native American genetic ancestry and HDL-cholesterol levels independent of socioeconomic factors in a representative sample of the Mexican population. METHODS We used data from the Mexican National Health Survey 2000, analyzing 1647 subjects from whom stored DNA samples and HDL measurements were available. To estimate proportional genetic ancestry (Native American, African, and European), we used a 107 genetic ancestry informative marker panel with the software STRUCTURE. To estimate the association between genetic ancestry and low HDL levels, we fitted logistic regression models with the percentage of Native American genetic ancestry, in quartiles, as the main predictor. RESULTS Mean HDL levels were 38.9 mg/dL, with 62% of subjects having levels below 40 mg/dL. Participants had on average 53.6% Native American, 39% European, and 7.3% African genetic ancestry. Those in the fourth quartile of Native American genetic ancestry had 35% higher odds of having low HDL-cholesterol relative to those in the first quartile (odds ratio, 1.35; 95% confidence interval, 0.99-1.81) after adjustment for socioeconomic level and other covariates, although the association is clearly nonlinear. CONCLUSION Native American genetic ancestry seems to play a small but distinct role in the development of low HDL cholesterol levels.
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Affiliation(s)
- Jimena Fritz
- Center for Population Health Research, National Institute of Public Health, Cuernavaca, Mexico
| | - Ruy Lopez-Ridaura
- Center for Population Health Research, National Institute of Public Health, Cuernavaca, Mexico
| | - Shweta Choudhry
- Human Genetics at Lung Biology Center, University of California San Francisco, San Francisco, California, USA
| | - Christian Razo
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
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Norris ET, Rishishwar L, Chande AT, Conley AB, Ye K, Valderrama-Aguirre A, Jordan IK. Admixture-enabled selection for rapid adaptive evolution in the Americas. Genome Biol 2020; 21:29. [PMID: 32028992 PMCID: PMC7006128 DOI: 10.1186/s13059-020-1946-2] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Accepted: 01/24/2020] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Admixture occurs when previously isolated populations come together and exchange genetic material. We hypothesize that admixture can enable rapid adaptive evolution in human populations by introducing novel genetic variants (haplotypes) at intermediate frequencies, and we test this hypothesis through the analysis of whole genome sequences sampled from admixed Latin American populations in Colombia, Mexico, Peru, and Puerto Rico. RESULTS Our screen for admixture-enabled selection relies on the identification of loci that contain more or less ancestry from a given source population than would be expected given the genome-wide ancestry frequencies. We employ a combined evidence approach to evaluate levels of ancestry enrichment at single loci across multiple populations and multiple loci that function together to encode polygenic traits. We find cross-population signals of African ancestry enrichment at the major histocompatibility locus on chromosome 6, consistent with admixture-enabled selection for enhanced adaptive immune response. Several of the human leukocyte antigen genes at this locus, such as HLA-A, HLA-DRB51, and HLA-DRB5, show independent evidence of positive selection prior to admixture, based on extended haplotype homozygosity in African populations. A number of traits related to inflammation, blood metabolites, and both the innate and adaptive immune system show evidence of admixture-enabled polygenic selection in Latin American populations. CONCLUSIONS The results reported here, considered together with the ubiquity of admixture in human evolution, suggest that admixture serves as a fundamental mechanism that drives rapid adaptive evolution in human populations.
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Affiliation(s)
- Emily T. Norris
- School of Biological Sciences, Georgia Institute of Technology, 950 Atlantic Drive, Atlanta, GA 30332 USA
- IHRC-Georgia Tech Applied Bioinformatics Laboratory, Atlanta, GA USA
- PanAmerican Bioinformatics Institute, Cali, Valle del Cauca Colombia
| | - Lavanya Rishishwar
- School of Biological Sciences, Georgia Institute of Technology, 950 Atlantic Drive, Atlanta, GA 30332 USA
- IHRC-Georgia Tech Applied Bioinformatics Laboratory, Atlanta, GA USA
- PanAmerican Bioinformatics Institute, Cali, Valle del Cauca Colombia
| | - Aroon T. Chande
- School of Biological Sciences, Georgia Institute of Technology, 950 Atlantic Drive, Atlanta, GA 30332 USA
- IHRC-Georgia Tech Applied Bioinformatics Laboratory, Atlanta, GA USA
- PanAmerican Bioinformatics Institute, Cali, Valle del Cauca Colombia
| | - Andrew B. Conley
- IHRC-Georgia Tech Applied Bioinformatics Laboratory, Atlanta, GA USA
- PanAmerican Bioinformatics Institute, Cali, Valle del Cauca Colombia
| | - Kaixiong Ye
- Department of Genetics, University of Georgia, Athens, GA USA
- Institute of Bioinformatics, University of Georgia, Athens, GA USA
| | - Augusto Valderrama-Aguirre
- PanAmerican Bioinformatics Institute, Cali, Valle del Cauca Colombia
- Biomedical Research Institute (COL0082529), Cali, Colombia
- Universidad Santiago de Cali, Cali, Colombia
| | - I. King Jordan
- School of Biological Sciences, Georgia Institute of Technology, 950 Atlantic Drive, Atlanta, GA 30332 USA
- IHRC-Georgia Tech Applied Bioinformatics Laboratory, Atlanta, GA USA
- PanAmerican Bioinformatics Institute, Cali, Valle del Cauca Colombia
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10
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Filling in the Gaps: The Association between Intelligence and Both Color and Parent-Reported Ancestry in the National Longitudinal Survey of Youth 1997. PSYCH 2019. [DOI: 10.3390/psych1010017] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Little research has dealt with intragroup ancestry-related differences in intelligence in Black and White Americans. To help fill this gap, we examined the association between intelligence and both color and parent-reported ancestry using the NLSY97. We used a nationally-representative sample, a multidimensional measure of cognitive ability, and a sibling design. We found that African ancestry was negatively correlated with general mental ability scores among Whites (r = −0.038, N = 3603; corrected for attenuation, rc = −0.245). In contrast, the correlation between ability and parent-reported European ancestry was positive among Blacks (r = 0.137, N = 1788; rc = 0.344). Among Blacks, the correlation with darker skin color, an index of African ancestry, was negative (r = −0.112, N = 1455). These results remained with conspicuous controls. Among Blacks, both color and parent-reported European ancestry had independent effects on general cognitive ability (color: β = −0.104; ancestry: β = 0.118; N = 1445). These associations were more pronounced on g-loaded subtests, indicating a Jensen Effect for both color and ancestry (rs = 0.679 to 0.850). When we decomposed the color results for the African ancestry sample between and within families, we found an association between families, between singletons (β = −0.153; N = 814), and between full sibling pairs (β = −0.176; N = 225). However, we found no association between full siblings (β = 0.027; N = 225). Differential regression to the mean results indicated that the factors causing the mean group difference acted across the cognitive spectrum, with high-scoring African Americans no less affected than low-scoring ones. We tested for measurement invariance and found that strict factorial invariance was tenable. We then found that the weak version of Spearman’s hypothesis was tenable while the strong and contra versions were not. The results imply that the observed cognitive differences are primarily due to differences in g and that the Black-White mean difference is attributable to the same factors that cause differences within both groups. Further examination revealed comparable intraclass correlations and absolute differences for Black and White full siblings. This implied that the non-shared environmental variance components were similar in magnitude for both Blacks and Whites.
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